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Reverse Coarse-Graining for Equation-Free Modeling: Application to Multiscale Molecular Dynamics.

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This study introduces a multiscale factorization method to reconstruct atom-resolved molecular dynamics from low-resolution data. It accurately simulates proteins by coupling coarse-grained and all-atom scales using nonlinear optimization.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Materials science

Background:

  • Reconstructing atom-resolved states from low-resolution data is crucial for understanding molecular behavior.
  • Macromolecular systems exhibit complex interactions across atomic and coarse-grained scales.

Purpose of the Study:

  • To develop and validate a multiscale factorization method for constructing atom-resolved states from low-resolution molecular dynamics data.
  • To effectively capture and manage the crosstalk between different scales in simulations.

Main Methods:

  • Utilized Trotter factorization to decouple all-atom and coarse-grained phases.
  • Employed short molecular dynamics runs for coarse-grained variable advancement.
  • Solved the all-atom microstate recovery as a nonlinear optimization problem using a quasi-Newton method.

Main Results:

  • The method successfully recovers a Boltzmann-relevant all-atom microstate consistent with updated coarse-grained variables.
  • Preserves both the coarse-grained representation and key fine-scale features.
  • Demonstrates accuracy and scalability for simulating proteins and their assemblies.

Conclusions:

  • The proposed multiscale factorization approach accurately and efficiently simulates complex macromolecular systems.
  • This method provides a scalable pathway for integrating atom-resolved details within coarse-grained molecular dynamics frameworks.